Radio resource allocation in LTE using utility functions based on moving average rates

In this paper, we propose a new algorithm to solve the downlink resource allocation problem in LTE networks taking the channel conditions into account. We first formulate the problem as a convex optimization problem, which maximizes the aggregated utility of all users. Different from other papers of the same topic, we construct the utility function based on the Exponential Moving Average (EMA) rate instead of the instantaneous data rate. The advantage of this approach is that it guarantees the users with very bad channel conditions still to be scheduled, even if the number of Physical Resource Blocks (PRBs) is smaller than the number of users. The problem is solved optimally with the Lagrangian decomposition method. Extensive simulations have been carried out to compare our approach to the instantaneous data rate approach and to analyze the influence of the system parameters on the behavior of the algorithm.